City of Bayside

Population - 2016

‘Estimated Resident Population’ is the estimate of the population of the area at June 30th in the year of the last Census, and updated annually with a preliminary estimate thereafter, until the next Census data are available. It is derived for small areas from experimental estimates of SA1 level ERP provided by the Australian Bureau of Statistics. For the purposes of allocating SA1s to small areas in years subsequent to the Census year, the relative population distribution per SA1 is assumed to be the same as it was in the Census year, even where growth has occurred. For this reason, populations for small areas may not match exactly what would be derived from the new Census counts in the interim years. Nevertheless, they are regarded as more accurate than the Census counts and are intended to give a good idea of the growth since the last Census in the small area.

Estimated Resident Populations for small areas should match closely the population estimate for the last Census (currently 2016) in forecast.id, however in subsequent years, there may be a mismatch between the population shown here for the most recent year, and that shown in forecast.id. This will be reconciled after the next Census data are released.

‘Usual Resident Population’ refers to the count of persons in the Census based on the place within Australia where they live or intend to live for 6 months or more in the Census reference year. It is generally lower than the Estimated Resident Population, even in the Census year, as it excludes people who are overseas on Census night, and also excludes the Census undercount, generally around 1-2% of the population.

‘Enumerated population’ refers to the count of persons staying in the area on Census night, regardless of where they usually live. For the purposes of this table, they exclude Overseas Visitors, however, which are shown separately. The enumerated population may be higher or lower than Usual Resident Population, depending on whether an area attracts many visitors or largely has people absent on Census night. It is generally, but not always, lower than the Estimated Resident Population, as it also excludes those overseas on Census night, and the Census undercount. In some cases, it may be higher than the Estimated Resident Population, for areas which receive a lot of visitors.

All subpopulations are based on place of usual residence except for the Overseas Visitors category, which is based on place of enumeration.

‘Eligible voters’ includes all Australian citizens over the age of 18 on Census day.

‘Overseas Visitors’ includes all people whose usual residence is outside Australia, and who plan to be in Australia for less than 12 months. They are normally excluded from all tables within profile.id but are included separately here for reference. This item relates only to enumerated population, as by definition there are no usual residents who are overseas visitors.

‘Population over 15’ includes all persons aged 15 and over in the area. It is used as the base population for many Census topics, including post-school education, employment and volunteering.

‘Employed population’ includes all persons over the age of 15 who had a job during the week prior to Census. It is used as the base population for many employment related topics such as Industry, Occupation and Method of Travel to Work.

‘Aboriginal and Torres Strait Islander population’ includes all persons who answered question 7 on the Census form “Is the person of Aboriginal or Torres Strait Islander origin?” with either “Yes, Aboriginal”, “Yes, Torres Strait Islander” or both. It is not derived from the “Australian Aboriginal” response to the Ancestry question, and this population can have any birthplace.

All dwelling counts are based on place of enumeration.

‘Total dwellings’ includes both private and non-private dwellings. All dwellings data are based on place of enumeration.

'Average household size’ consists of the number of persons counted in private dwellings divided by the number of occupied private dwellings on Census night.

Service age groups

Derived from the Census question:

'What is the person's date of birth or age?'

Groups the population by age into categories which reflect a similar life stage or service user profiles.

Includes all persons except 'Overseas Visitors'.

0-4 Babies and pre-schoolers

5-11 Primary Schoolers

12-17 Secondary Schoolers

18-24 Tertiary education and transition to independence

25-34 Young workforce

35-49 Parents and homebuilders

50-59 Older workforce and emerging empty nesters

60-69 Empty nesters and retirees

70-84 Seniors

85+ Frail aged

If an answer to the Age question is not provided, the Australian Bureau of Statistics imputes the age of the respondent, so there is no "Not stated" category for this variable. This also applies if a dwelling is identified as occupied but no form is returned.

Five year age groups

Derived from the Census question:

Five year age groups provide equal age cohorts enabling direct comparison between all ages without distortion.

Includes all persons except 'Overseas Visitors'.

If an answer to the Age question is not provided, the ABS imputes the age of the respondent, so there is no "Not stated" category for this variable. This also applies if a dwelling is identified as occupied but no form is returned.

Single year of age

Derived from the Census question:

'What is the person's date of birth (or age last birthday)?'

Presents single year of age data in an age-sex pyramid

Includes all persons except 'Overseas Visitors'.

Enables the identification of small groups and small changes in age structure over time as well as comparison by gender. Males appear on the left of the chart, and females presented to the same scale appear on the right of the chart.

If an answer to the Age question is not provided, the Australian Bureau of Statistics imputes the age of the respondent, so there is no "Not stated" category for this variable. This also applies if a dwelling is identified as occupied but no form is returned.

Please note that due to a change in the method of perturbation in 2016 (removing additivity), there are significant introduced errors in the single year of age data, which no longer adds to the total for the area of interest. It is considered that this difference is minimal at the Local Government Area level and above, but for small areas, adjustments in the data to protect confidentiality in 2016 are too large to present this data. As a result, Single Year of Age is now only available for the primary geography, not for small areas. Small area data are still available in the data exporter, but please use this with caution, as they will not add to the same totals as other age group categories.

Ancestry

Derived from the Census question:

'What is the person's ancestry?'

Multi-response

Ancestry data are coded using the Australian Standard Classification of Cultural and Ethnic Groups (ASCCEG).

Includes all persons.

There is an element of subjectivity to ancestry, which is not present in birthplace or language data. Ancestry can represent a person's understanding of their own affiliations, rather than any objective measure of genealogy.

'Other Southern and East African' includes Kenyan, Oromo, Tanzanian, Ugandan, Zambian and others.

'Inadequately Described' includes 'African, so described', 'Asian, so described' and 'European, so described'.

Please note the following issues with specific ancestry groups:

'Cypriot' was not collected in 2001. For the 2001 series Cypriot is included in 'Other Southern/Eastern European' which makes this category not directly comparable between 2001 and later years.

'Burmese peoples' includes Burmese, Anglo-Burmese, Mon, Karen and Chin. Karen was not separately identified in 2001 and Chin was not in 2006. Both are identified in 2011 and 2016. These are two significant emerging groups in Australia, but have been combined into 'Burmese peoples' to enable comparisons with earlier years.

'Serbian/Yugoslavian' includes "Serbian" and "South Eastern European, nfd", which contains primarily people who in 2011 stated their ancestry as "Yugoslavian". Previously these were coded to "Serbian", so the categories have been combined for comparability in 2011 and 2016.

'Bengali/Bangladeshi' includes 'Bengali' and 'Bangladeshi'. People who responded 'Bangladeshi' in 2006 were coded to 'Bengali' so the two categories have been combined for comparability in 2011 and 2016.

'Sri Lankan/Sinhalese' includes 'Sri Lankan' and 'Sinhalese'. Sri Lankan ancestry was not collected prior to 2011, so it is combined in 2011 and 2016 for time series comparability.

Respondents can nominate up to two ancestries, and data are presented as multi-response. The numbers are a count of individual responses, but the percentages are expressed as a proportion of all people, meaning individuals can be counted twice in the table and percentages can add to more than 100%.

Please note that the categories "Australian Aboriginal" and "Torres Strait Islander" in the Ancestry classification should not be used as estimates of the populations of these groups in the area. A majority of Aboriginal Australians do not write in this ancestry in the Ancestry question, instead marking the "Australian" box on the Census form. This means that the ancestry "Australian Aboriginal" is a significant undercount of the true indigenous population. A specific question relating to indigenous (ATSI) status is included on the Census, which is a much better measure of this population (though still generaly considered an undercount). For this population, please see the Population page on profile.id.

IMPORTANT NOTE ABOUT COUNTING RESPONSES

Please note that the 'Other ancestry' category in the table is not entirely a count of responses, nor entirely a count of persons. A total of 125 ancestry groupings were ordered from the ABS, covering most of the major ancestries included in the population. For the 'Other' categories mentioned above, if a respondent nominated two ancestries which both fall into the same 'other' category, they are only counted once in this table. However if they nominated ancestries which fell into two different categories in this table, they are counted twice. This includes ancestries which have had to be combined in 2011 and 2016 for time series comparability, such as Sudanese.

For example if a person nominated two ancestries, 'Nuer' and 'Darfurian', these would be counted in the table as a single response in the category 'Sudanese'. However if the person had nominated 'Nuer' and 'Morroccan', they would be counted as two responses in the table, once in 'Sudanese' and once in 'Other Arab Peoples'. Though the number of potential combinations which have this issue is large, they mostly represent unlikely combinations of ancestries, and for the most part, ancestries have been included in 'Other' categories due to their very low number of responses anyway. For this reason, the issue is likely to have a negligible effect on the data. Generally about 15-20% of the population nominate more than one ancestry.

Derived from the Census question:

The top 10 countries of birth for the selected area are shown in this table. The table is generated from a list of 125 birthplaces which make up 99.2% of the overseas-born population of Australia. These birthplaces have been defined to enable direct comparison over time back to 1991, with the exceptions listed below. It is possible that a country of birth from outside this top 125 would feature in the top 10 list if it was separately included, but at present these are only shown in the 'Total Overseas Born' category. All 125 countries of birth are available in the Data Exporter section on this site. The full list of approximately 300 countries of birth is available on request from .id.

'Serbia/Montenegro (fmr Republic of Yugoslavia)' includes Serbia and Montenegro, as well as 'South Eastern Europe nfd' in 2016, 2011 and 2006. Those people categorised to South Eastern Europe were primarily those who stated their birthplace as Yugoslavia, which no longer exists as a nation. In 2001 it includes all people who listed their birthplace as Yugoslavia, while it is not available for 1996 and 1991 due to considerable changes to national boundaries in this region.

'China' excludes Taiwan, Macau and Hong Kong.

'Sudan' includes South Sudan. South Sudan is a new country which declared independence in 2011 and was recorded in the 2011 and 2016 Census. For comparison with earlier Census years, data has been recombined for 2011 and 2016 standard output.

'Bhutan' was available as a country of birth in 2006 and earlier years but has not been included in the profile for these years due to very small numbers in Australia. In 2006, there were only 137 people from Bhutan in Australia. It is included in 2011 and 2016.

'Main English speaking countries' includes Canada, Ireland, New Zealand, South Africa, the United Kingdom, and the United States of America. This category is under review and may be altered at a later date.

'Non-English speaking backgrounds' refers to persons born in countries not included in 'Main English speaking countries'.

'Not Stated' includes 'Inadequately Described' and 'At sea'.

‘Inadequately Described’ includes people whose responses could not be coded to a category and those who were born 'At sea'.

Proficiency in English

Derived from the Census question:

English proficiency aims to measure the ability of persons who speak English as a Second Language to also speak English.

Includes all persons who speak a language other than English at home.

Excludes people who speak English at home.

When viewed with other ethnic and cultural indicators, the data tends to reflect the ethnic composition of the population and the number of years of residence in Australia.

In general, an area with a high proportion of migrants who have lived in Australia for many years, and/or have higher education levels, will have a higher proportion of those who speak English well or very well. Conversely, an area with many recent non-English speaking migrants, from lower socio-economic backgrounds (particularly refugees) will often have a higher proportion of those who speak English not well or not at all.

Note: A person's English proficiency is based on a subjective assessment and should therefore be treated with caution.

Responses to the question on Proficiency in English in the Census are subjective. For example, one respondent may consider that a response of 'Well' is appropriate if they can communicate well enough to do the shopping, while another respondent may consider such a response appropriate only for people who can hold a social conversation. Proficiency in English should be considered as an indicator of a person's ability to speak English and not a definitive measure of this ability.

Language spoken at home is designed to measure 'first' or 'native' language, though some migrants who have been in Australia for many years may speak English at home is recorded.

Includes all persons.

Excludes multi-lingual populations. E.g. If I speak English and French, but mainly speak English at home, the fact that I speak French is not captured.

The top 10 languages are shown provided they have more than 20 speakers. These top 10 are sorted from a list of 100 languages which combined make up 98.5% of the non-English speaking population of Australia. The full list of over 500 languages is available on request from .id.

'Not stated' includes the category 'Inadequately described'.

Some languages are not available for earlier Census years. Issues are as follows:

'Tagalog' includes Filipino, which was recorded as a separate language from Tagalog in 2006 and later years, but no such distinction was made in earlier Censuses. Filipino is a standardised version of Tagalog, incorporating words from other indigenous languages within the Philippines.

'Persian' includes Dari, which was recorded as a separate language from Persian in the 2006 and later Censuses, but no distinction was made in earlier Censuses. Dari is a localised name for Persian in Afghanistan.

'Min Nan' was recorded in 2011 to represent the languages previously recorded as Hokkien and Teochew, correctly classifying these as a single language. For comparability, Hokkien and Teochew have been combined in earlier Censuses.

'Assyrian/Aramaic' includes Assyrian, Chaldean and Aramaic languages.

'African Languages, nec' is no longer available due to the separation of many African languages into their own categories. These separated African languages are not available in time series.

Please note that due to substantial changes in the language classification between 1991 and 1996, it is not possible to provide data on the full list of languages in 1991. The classification is non-comparable, so when 1991 is selected, only “Speaks English only” and “Non-English total” are provided.

Religion

Derived from the Census question:

The religion question in the Census is an optional question and so has a relatively high rate of 'Not Stated' responses.

Includes all persons.

The classification for Religion has changed significantly over the last 20 years. To make it possible to compare religious affiliation over time the full list of 140 religions has been aggregated into 46 categories. The top 10 religious groups for the City of Bayside are presented from the aggregated list. All 46 categories are available in the Data Exporter on this site and the full list of 140 religions collected in the Census is available from .id on request.

'Non Classifiable Religious Belief' includes Theism, 'Not Defined', ‘Own Spiritual Beliefs’, and ‘Secular beliefs not elsewhere classified’. Anyone who stated their religion as ‘Jedi’ or other Star Wars reference is also included in this category.

Individual income

Derived from the Census question:

Individual income data presents the total gross income (including pensions and allowances) that a person usually receives each week.

The Census question also lists a number of items to include or not include.

Applies to all persons aged 15 years and over.

Only 2016 data are presented for this topic as income ranges are altered every five years to adjust for inflation and wages growth so comparison over time is not possible. Please see the income quartiles for change over time.

Derived from the Census question:

Individual income categories are not comparable over time because of the influences of economic change such as inflation. Income quartiles are the most objective method of comparing change in the income profile of a community over time.

Individual income quartiles look at the distribution of incomes in the area of interest relative to Victoria. Income quartiles are created for Victoria by ranking individuals from the lowest incomes to the highest incomes and then dividing the list into four equal groups or quartiles. This is repeated for each Census period. The table shows the income categories for each quartile in each Census period.

For the purposes of calculating quartiles, individuals not stating their income in the Census are excluded.

Enumerated quartile group dollar ranges (Individuals)

Calculated from income data for Victoria

Weekly income by Census year

Individual quartile ranges

2016

2011

2006

2001

1996

1991

Lowest group

$0 to $309

$0 to $261

$0 to $204

$0 to $180

$0 to $144

$0 to $124

Medium lowest

$310 to $645

$262 to $561

$205 to $456

$181 to $380

$145 to $290

$125 to $274

Medium highest

$646 to $1,198

$562 to $1,059

$457 to $859

$381 to $689

$291 to $545

$275 to $482

Highest group

$1,199 and over

$1,060 and over

$860 and over

$690 and over

$546 and over

$483 and over

The analysis shows the number and proportion of individuals in the City of Bayside falling into each of the four quartiles. This gives a clear picture of how incomes in the City of Bayside compare to Victoria. In Victoria 25% of persons fall into each category by definition. If, for example, the the City of Bayside has 35% in the top category and only 15% in the lowest, this indicates that the the City of Bayside has proportionally more high income individuals and less low income individuals.

More importantly, the dataset for Victoria is grouped into those four equal categories for each Census back to 1991 independently. Repeating this process for each Census period, enables a comparison of areas over time, because the quartile becomes a constant, regardless of the dollar amounts involved enabling you to track change in a local area independent of inflation. For example, if the City of Bayside has had an increase in the number of individuals in the top income quartile, this indicates that incomes are increasing in real terms, relative to other parts of the State.

Household income

Derived from the Census question:

'What is the total of all wages/salaries, government benefits, pensions, allowances and other income the person usually receives?'

Household income data presents the total weekly incomes of all persons over the age of 15 in the household.

Excludes 'Other non-classifiable households'.

Only 2016 data are presented for this topic as income ranges are altered every five years to adjust for inflation and wages growth so comparison over time is not possible.

‘Not Stated’ includes any household where at least one person aged 15 years and over did not state an income and/or at least one household member aged 15 years and over was temporarily absent. In these cases, the aggregate of all stated individual incomes would be less than the true household income so these households are excluded from the calculation.

As individual income is collected in ranges, in order to calculate household income, a dollar value has to be imputed by the ABS to each range, then the individual incomes are aggregated, and output into ranges again. There is an inherent uncertainty in this process, so household incomes should only be treated as a guide to the income level in an area, not an exact calculation.

Derived from the Census question:

Household income categories are not comparable over time because of the influences of economic change such as inflation. Income quartiles are the most objective method of comparing change in the income profile of a community over time.

Household income quartiles look at the distribution of incomes in the area of interest relative to Victoria. Income quartiles are created for Victoria by ranking households from the lowest incomes to the highest incomes and then dividing the list into four equal groups or quartiles. This is repeated for each Census period. The table shows the income categories for each quartile in each Census period.

For the purposes of calculating quartiles, households not stating their income in the Census are excluded.

Quartile group dollar ranges (Households)

Calculated from income data for Victoria

Weekly income by Census year

Household income ranges

2016

2011

2006

2001

1996

1991

Lowest group

$0 to $740

$0 to $624

$0 to $539

$0 to $426

$0 to $340

$0 to $309

Medium lowest

$741 to $1,416

$625 to $1,213

$540 to $1,021

$427 to $812

$341 to $640

$310 to $575

Medium highest

$1,417 to $2,394

$1,214 to $2,148

$1,022 to $1,682

$813 to $1,379

$641 to $1,075

$576 to $936

Highest group

$2,395 and over

$2,149 and over

$1,683 and over

$1,380 and over

$1,076 and over

$937 and over

The analysis shows the number and proportion of households in the City of Bayside falling into each of the four quartiles. This gives a clear picture of how incomes in the City of Bayside compare to Victoria. In Victoria 25% of households fall into each category by definition. If for example, the City of Bayside has 35% in the top category and only 15% in the lowest, this indicates that the City of Bayside has proportionally more high income households and less low income households.

More importantly, the dataset for Victoria is grouped into those four equal categories for each Census back to 1991 independently. Repeating this process for each Census period, enables a comparison of areas over time, because the quartile becomes a constant, regardless of the dollar amounts involved enabling you to track change in a local area independent of inflation. For example, if the City of Bayside has had an increase in the number of households in the top income quartile, this indicates that incomes are increasing in real terms, relative to other parts of the State.

Equivalised household income quartiles

Derived from the Census question:

'What is the total of all wages/salaries, government benefits, pensions, allowances and other income the person usually receives?'

Equivalised household income can be viewed as an indicator of the economic resources available to a standardised household.

For a lone person household equivalised income is equal to household income. For a household comprising more than one person, it is an indicator of the household income that would be needed by a lone person household to enjoy the same level of economic wellbeing.

As an example, consider the case of a family of two adults, and three children aged 8, 13 and 16. If they have a household income of $2,000 per week, it is clearly not reasonable to compare their income to that of a lone person household with an income of $2,000 per week who would have far less living expenses. However it is also not reasonable to simply divide the income by the five people in the household, as there are economies of scale in larger households.

This is why equivalised household income divides the household income by an equivalence factor, according to the 'modified OECD' equivalence scale. This factor is derived by adding the following:

First Adult + 1

Second and subsequent adults, and children over 15 +0.5

Children under 15 + 0.3

So our family of 5 would have an equivalence factor of 2.6 (1 for the first adult, 2 additional adults at 0.5, and 2 children under 15 at 0.3). Income is divided by this to arrive at the equivalised household income, which in this case would be $769. This is the income a lone person would need to have to be equivalent in living standards to this family of five.

Because it is only RELATIVE equivalised income that matters, rather than the actual dollar amount, only income quartiles are presented on this page. For details of how quartiles are calculated and used, please see the data notes for Household income quartiles.

Highest qualification achieved

Derived from the Census question:

'What is the level of the highest qualification the person has completed?'

This topic includes all persons aged 15 years and over. It relates to the level of the highest qualification achieved excluding school-based qualifications, as of Census day.

Qualification levels are presented in descending order (of educational and time requirements), with Postgraduate Degrees being the highest, and “No qualification” the lowest. To be included, qualifications must be within scope of the question – that is, recognised by or equivalent to a qualification by an Australian university or tertiary institution.

‘Vocational’ includes all Certificate level qualifications, usually associated with trades. Note that it is not always necessary to have completed year 12 to obtain a Certificate level qualification, so the total of those with non-school qualifications should not be taken as the number of people who have completed year 12. This is contained within the “Highest level of schooling” topic.

Need for assistance

Derived from the Census questions:

'Does the person ever need someone to help with, or be with them for, self care activities?', 'Does the person ever need someone to help with, or be with them for, body movement activities?', 'Does the person ever need someone to help with, or be with them for, communication activities?', and 'What are the reasons for the need for assistance or supervision shown in questions 20, 21 and 22?' (as per above).

This data identifies people who report a need for assistance due to a 'profound or severe core activity limitation'. This population is defined as people who need assistance in their day to day lives with any or all of the following activities – self-care, body movements or communication – because of a disability, long-term health condition, or old age.

This question relies on people evaluating themselves, (or their carers), as being in need of assistance. Consequently, this question provides an indication of the characteristics of people who report, or are reported as requiring, a need for assistance; but cannot be relied upon to provide details as to the total number of people with a 'profound or severe core activity limitation'.

Persons under the age of 40 whose only stated reason for need for assistance was ‘old or young age’ are included under ‘no need for assistance’.

This should not be viewed as the total population with a disability, as many people with a disability do not require assistance, and would therefore likely answer "no" to this question. For more information on types and levels of disability (including those not requiring assistance) please refer to the ABS publication 4430.0, Survey of Disability, Ageing and Carers.

Unpaid childcare

Derived from the Census question:

'In the last two weeks did the person spend time looking after a child, without pay?', which specifically asks respondents to differentiate between caring for their own children and caring for others children.

Only 2016, 2011 and 2006 data are available for this topic as the question was only asked for the first time in 2006.

Includes all persons aged 15 years and over.

Includes the time a person spends caring for a child or children under the age of 15 without being paid, in the two weeks prior to Census.

Excludes caring for children in a paid capacity (e.g. at a child care centre.

'Cared for own child/ren' includes people caring for their own children, whether they usually live with them or not.

'Cared for other child/ren' can include people looking after their own grandchildren or the children of other relatives or the children of friends or neighbours, or involved in unpaid family day care.

Labour force status

Derived from the Census question:

'Last week did the person have a full time or part time job of any kind?'

This topic includes persons aged 15 years and over, and assesses employment in the week prior to the Census.

It is actually derived from 5 Census questions (34, 35, 44, 46 and 47), which look at whether the respondent had a job, if not, whether they were looking for work, and if they were looking for work whether they were able to start in the past week.

To classify full or part-time work, the question on hours worked is also used.

'Employed full time' means having worked 35 hours or more in all jobs.

'Employed part time' means having worked less than 35 hours in all jobs.

Please note that the full or part-time status refers only to the week before Census, not to a ‘usual’ number of hours.

The category of ‘Employed – away from work’ was only available since the 2006 Census. The ABS categorises persons away from work as either employed full time or part time based on usual hours worked. The Census only uses actual hours worked (Q44) to determine whether someone is employed full-time or part-time and a response to Q34 to determine whether they were employed, but away from work. To enable time series comparisons in profile.id, this category has been combined with ‘Employed part-time’.

The 'Labour force' is all persons aged 15 years and over who are either employed or looking for work and available to start. Both full and part-time work counts towards the labour force.

The percentages in the first table, showing employed and unemployed, are expressed as a percentage of those who are in the labour force.

The ‘Unemployment Rate’ is defined as the number of unemployed persons (looking for work and available to start) as a percentage of the labour force. The percentage for ‘Unemployed’ in profile.id is the same as the unemployment rate.

The ‘Participation Rate’ is defined as the labour force expressed as a percentage of the total population aged 15+. In profile.id, the percentage in the ‘Total labour force’ category in the second table can be regarded as the participation rate. Note, however that it is not directly comparable to participation rates derived from the ABS labour force monthly survey, because a proportion of the population (5.6% nationally in 2011) don’t state their labour force status. For this reason, Census participation rates are likely to be a little lower than those derived from the survey, but they are comparable over time and across geographic areas with other Census data.

The occupation classification is updated periodically to take account of emerging occupation groups and changes to the structure of the labour force. The most recent change was in 2006.

Please note that it is not possible to derive an unemployment rate for a specific occupation (eg. how many unemployed truck drivers are there?). This is because occupation is only collected for those who are actually employed. An unemployed person by definition does not have an occupation.

Method of travel to work

Derived from the Census question:

Method of travel to work relates specifically to the journey to work on the morning of Census day (or later that day for shift workers).

This topic includes only to people aged 15 and over who were employed in the week prior to Census.

Respondents can nominate up to three modes of travel. Because this results in 234 discrete categories based on combinations of 1,2 or 3 modes, this is an unwieldy dataset. For the purposes of profile.id, we have aggregated them into single methods, where certain methods override others. Aggregations are as follows:

'Train' includes any journey involving a train, whether or not other methods were used.

'Bus' includes any journey involving a bus, except for those also involving a train.

‘Tram or Ferry’ includes any journey involving a tram or ferry, except for those involving bus or train. 'Tram' includes light rail. In the 1996 and 1991 Census years, Tram and Ferry were combined as one item, so it is necessary to recombine them in later years in profile.id for reasons of comparability over time.

'Other' refers to any method not listed in the standard categories, plus any combination of two or three methods NOT involving a bus, train, tram or ferry.

The remaining categories refer to a single method of travel (e.g. 'Car as driver' when no other method was used).

'Walked only', 'Worked at home' and 'Did not go to work' are exclusive and never presented in combination with other methods. Where multiple responses are provided on the Census form, which include one of these, these methods override the others.

Further breakdowns of combinations of method of travel to work are available on request from .id for our Local Government Clients, or from the ABS.

Households summary

Derived from the Census question:

‘What is the person’s relationship (to each other person in the household)?’

Describes the type of family and non-family households within a dwelling.

Includes all households within occupied private dwellings.

Excludes persons counted in non-private dwellings

'A household' is a group of people living in a private dwelling making shared provision for meals.

'A family' is a group of people living in a private dwelling who are related by blood or marriage (including de-facto marriage and same-sex couples).

Households may contain up to three families each with a different family composition. Family households in this table are classified into broad family type by the family composition of the primary family only. This significantly simplifies the reading of the table. Multiple family households make up a very small proportion of all households (less than 2% nationwide) so this simplification is expected to have negligible effect on the output.

Household data are based on place of enumeration only – people recorded as being temporarily absent from households are included for the purposes of assessing household composition, but where the entire household was away on Census night, residents are not moved back into households by the usual resident process (unoccupied dwellings remain unoccupied).

'Other families' includes any household of related individuals where a parent-child or couple relationship does not exist (e.g. siblings, uncle/nephew, grandparent-grandchild).

'Group household' includes any household consisting of two or more unrelated individuals.

'Visitor only households' includes all households where there were no usual residents of the dwelling present (i.e. all persons in the household were resident elsewhere). An example of this would be a family staying in a holiday apartment. No family information is recorded in this case.

'Other not classifiable' households consist mainly of dwellings which the Census Field Officer believes were occupied on Census night but from which no form was returned. People are imputed into these households with most responses set to “Not Stated” (but age, sex and marital status are imputed). A small proportion of households in this category are those where only children aged under 15 were present on Census night (no adults).

Same sex couple families are included in this table but not separately identified.

For more information on household and family type, please refer to the data quality statements for Family Household Composition on the ABS website.

Households with children by life stage

Derived from the Census question:

‘What is the person’s relationship (to each other person in the household)?’

Presents a subset of household/family type data, based on those households who have children.

Includes households, by the family type of the primary family in the dwelling. Where there is more than one family in a household, the type of family is coded by the "primary family", which is normally the first family recorded on the Census form.

Excludes 'Overseas visitors', but people temporarily absent from households are included in the Census when assessing the household type (e.g. a couple family with an absent partner is still recorded as a couple family if the partner's details are recorded in the "persons temporarily absent" field).

'Children' include either children under 15 (dependent by definition), dependent students aged 15-24, or independent children who are either non-students aged 15-24, or anyone over the age of 25. To be counted in this table, a parent-child relationship must exist in the household.

Couples and single parent families are broken into three 'life stages' based entirely on the age of the children. The age of parents is not a factor in this classification:

'Young children' includes households where all children are aged under 15.

'Mixed age children' includes households where there are children (two or more) both aged under 15, and 15 or over.

'Older children' includes households where all children are aged 15 or over. This can include adult-non dependent children.

Note that to be included in the 'Mixed age children' category a household MUST have more than one child present. A household with one child would move directly from the 'Young children' to the 'Older children' category under this classification.

For more general information about the classification of households in profile.id®, please see the data notes for the Household Summary table.

Households without children by life stage

Derived from the Census question:

‘What is the person’s relationship (to each other person in the household)?’

Presents a subset of household/family type data, based on couple and lone person households without children.

Includes same-sex couples.

Couples and lone persons are broken into three 'life stages' based on the age of the household reference person. The household reference person is normally 'Person 1' on the Census form, and relationships in the household are defined by reference to this person. Where a child or visitor to the household is listed as person 1, the ABS allocates a different individual on the form to be the household reference person. In the case of a lone person household, the lone person is the household reference person. In the case of a couple, it may be either adult. It is no indication of household headship.

'Young' includes households where the household reference person is aged 15-44.

'Middle-aged' includes households where the household reference person is aged 45-64.

'Older' includes households where the household reference person is aged 65+

For more general information about the classification of households in profile.id®, please see the data notes for the 'Household Summary' table.

Household size

Derived from the three Census questions:

'Name of each person including visitors who spent the night of Tuesday, 9 August 2016 in this dwelling', and 'Where does the person usually live?', and 'Name of each person who usually lives in this dwelling but was away on Tuesday, 9 August 2016.'

Counts households by the number of persons usually resident on Census night.

Includes occupied private dwellings with at least one resident home on Census night.

Includes people who were at home on Census night, and up to three people listed as being temporarily absent from the dwelling.

Excludes people who were in the dwelling but not usually resident there (i.e. visitors).

Excludes households where the entire household was absent on Census night - the dwelling is either unoccupied or has visitors only. Also excludes “Other non-classifiable” households, which are mostly households where no Census form was returned.

Housing tenure

Derived from the Census questions:

'Is this dwelling (owned outright, owned with a mortgage etc.)', and 'If this dwelling is being rented, who is it rented from?'

Presents the tenure type of occupied private dwellings, and for those dwellings being rented, provides a breakdown of the type of landlord the dwelling is being rented from.

Includes occupied private dwellings.

'Fully owned' includes dwellings that are owned by its occupants in full, with no mortgage.

'Being purchased' includes all dwellings being paid off with a mortgage, as well as dwellings being purchased under a rent/buy scheme.

'Renting – social housing' includes households renting from a State/Territory Government housing authority (generally referred to as public housing) and households renting from a housing co-operative, community organisation or church group.

'Renting – private' refers to households renting from a real estate agent, a private person or an employer.

'Renting – not stated' refers to households who stated they were renting but did not state their landlord type.

'Other tenure type' includes life tenure schemes, squatting and other forms of occupancy.

Housing loan repayments

Derived from the Census questions:

'How much does your household pay for this dwelling?' and 'Is this dwelling (owned outright, owned with a mortgage etc.)'

Presents monthly housing loan repayments made by a household to purchase the dwelling in which the household was counted on Census night.

Includes households (occupied private dwellings) who are purchasing their dwelling with a mortgage or under a dwelling under a 'rent/buy' scheme.

Includes caravans if they have a mortgage.

Please note, that due to changes to the ABS Additivity rules, to protect confidentiality, for 2016 it is necessary to display Mortgage Repayments with a reduced set of ranges, compared to what has been available in previous Census years. For more information please see the “Data confidentiality” section.

Derived from the Census questions:

Housing loan repayment categories are not comparable over time because of the influences of inflation. The quartile method is the most objective method of comparing change in mortgage payments in an area over time.

Mortgage quartiles look at the distribution of mortgage payments among households paying off their home in the City of Bayside relative to Victoria. Mortgage quartiles are created for Victoria by ranking all mortgagor households from the lowest payments to the highest payments and then dividing the list into four equal groups or quartiles. This is repeated for each Census period. The table shows the payment categories for each quartile in each Census period.

Quartile group dollar ranges (Housing loan repayments)

Calculated from loan repayment data for Victoria

Monthly housing loan repayments by Census year

Household income ranges

2016

2011

2006

2001

1996

Lowest group

$0 to $1,133

$0 to $1,103

$0 to $831

$0 to $596

$0 to $502

Medium lowest

$1,134 to $1,702

$1,104 to $1,695

$832 to $1,261

$597 to $866

$503 to $750

Medium highest

$1,703 to $2,336

$1,696 to $2,351

$1,262 to $1,823

$867 to $1,208

$751 to $1,034

Highest group

$2,337 and over

$2,352 and over

$1,824 and over

$1,209 and over

$1,035 and over

The analysis shows the number and proportion of mortgagor households in the City of Bayside falling into each of the four quartiles.

This gives a clear picture of how mortgage payments in the City of Bayside compare to Victoria. In Victoria 25% of persons fall into each category by definition. If, for example, the City of Bayside has 35% in the bottom category and only 15% in the highest, this indicates that the the City of Bayside has proportionally more people paying low mortgage repayments relative to the State, and less high mortgage payments.

More importantly, the dataset for Victoria is grouped into those four equal categories for the 2016, 2011, 2006 and 2001 Census independently. Repeating this process for each Census period, enables a comparison of areas over time, because the quartile becomes a constant, regardless of the dollar amounts involved enabling you to track change in a local area independent of inflation. For example, if the City of Bayside has had an increase in the proportion of households in the top mortgage payment quartile, this indicates that perhaps a large cohort of the population have bought in recently or the area has opened up to first home buyers, or perhaps the price of homes has just increased.

Housing rental payments

Derived from the Census questions:

'How much does your household pay for this dwelling?' and 'Is this dwelling (owned outright, owned with a mortgage etc.)'

Presents weekly rent paid by for the dwelling in which they were counted on Census night.

Includes households (occupied private dwellings) renting their dwelling or occupying it rent free. Australia-wide 3.2% of dwellings being rented were paying no rent in 2016.

Includes caravans being rented.

Excludes 'Other not classifiable' households as no information about their tenure type is available.

Note: Rent is a better indicator of the value of housing in an area than mortgage repayments, as the rent paid is less dependent on when the occupants moved in, and there is no equity component which reduces the cost (rent-buy schemes are included as mortgages, not rent).

Please note, that due to changes to the ABS Additivity rules, to protect confidentiality, for 2016 it is necessary to display Rental Payments with a reduced set of ranges, compared to what has been available in previous Census years. For more information please see the “Data confidentiality” section.

Housing rental payment quartiles

Derived from the Census questions:

Rental payment categories are not comparable over time because of the influences of inflation. The quartile method is the most objective method of comparing change in the rental payments of an area over time.

Rental payment quartiles look at the distribution of rents among rented households in the City of Bayside relative to Victoria. Rental quartiles are created for Victoria by ranking all renting households from the lowest payments to the highest payments and then dividing the list into four equal groups or quartiles. This is repeated for each Census period. The table shows the payment categories for each quartile in each Census period.

Quartile group dollar ranges (Housing rental payments)

Calculated from rental payment data for Victoria

Weekly housing rental payments by Census year

Household income ranges

2016

2011

2006

2001

Lowest group

$0 to $245

$0 to $190

$0 to $133

$0 to $109

Medium lowest

$246 to $330

$191 to $279

$134 to $190

$110 to $156

Medium highest

$331 to $416

$280 to $362

$191 to $252

$157 to $205

Highest group

$417 and over

$363 and over

$253 and over

$206 and over

The analysis shows the number and proportion of renting households in the City of Bayside falling into each of the four quartiles. This gives a clear picture of how rents in the City of Bayside compare to Victoria. In Victoria 25% of persons fall into each category by definition. If, for example, the City of Bayside has 35% in the bottom category and only 15% in the highest, this indicates that the City of Bayside has proportionally more people paying low rents relative to the State, and less high rent payers.

More importantly, the dataset for Victoria is grouped into four equal categories for the 2016, 2011, 2006 and 2001 Census independently. Repeating this process for each Census period, enables a comparison of areas over time, because the quartile becomes a constant, regardless of the dollar amounts involved enabling you to track change in a local area independent of inflation. For example, if the City of Bayside has had an increase in the number of households in the top rent payment quartile, this indicates that perhaps the area is gentrifying with rents increasing faster than in other parts of the State.

Type of internet connection

Derived from the Census question:

'Does any member of this household access the internet from this dwelling'

This topic presents information about whether or not members of the household access the internet from the dwelling.

Only 2016 Census data are included in this topic, as the question wording changed considerably between 2011 and 2016 and it is no longer comparable. In 2011 and 2006, the question asked what type of internet connection the household had. In 2016 this changed to asking about access and whether any members of the household used the internet.

Internet access is quite high across Australia, at 79% of all households, but this variable also has a high not stated component, comprising 7.6% of all households.

Dwelling type

Derived from the Census:

'Dwelling Structure is derived from the ABS address register supplemented with information from Census Field Officers.'

Categorises the type and structure of dwellings.

Includes all private dwellings.

The categories used by the ABS are subject to systematic misinterpretation by Census collectors, particularly in determining the difference between semi-detached/townhouses and blocks of flats in 1-2 storey blocks. For this reason, to maintain consistency over time, the categories used here combine these two categories as 'medium density'. This creates a better measure of actual change over time in an area. We have applied the term 'density' here to the structure of the dwelling and not the number of dwellings per hectare.

In addition, in 2016, with the move to the Address Register as the uniform source for this information, there is a significant change between 2011 and 2016 in the numbers of dwellings in some of the categories. Nationally, there was a fall of approximately 128,000 dwellings recorded as “Flat Unit or Apartment in a 1 or 2 storey block”, and a corresponding increase in the Semi-Detached categories. Because .id combines these categories in “Medium Density”, there is relatively little change expected in the output on profile.id.

'Separate house' includes all free-standing dwellings separated from neighbouring dwellings by a gap of at least half a metre.

'Medium density' includes all semi-detached, row, terrace, townhouses and villa units, plus flats and apartments in blocks of 1 or 2 storeys, and flats attached to houses.

'High density' includes flats and apartments in 3 storey and larger blocks.

'Caravans, cabins, houseboats' includes all such mobile accommodation, both inside and outside caravan parks (including caravans in private backyards.

'Other' includes houses and flats attached to shops or offices, and improvised homes, tents and sleepers out on Census night.

'Unoccupied dwellings' are shown in a separate table. An unoccupied dwelling is a dwelling where the Census Collector determined that it was vacant on Census night. Where a collector cannot determine this, the dwelling is usually treated as occupied. Dwellings may be unoccupied for a variety of reasons including:

Seifa index of disadvantage

The SEIFA indexes are derived from Census data by a method called Principal Component Analysis which is a regression technique that derives an index from a set of variables related to the concept of disadvantage, based on the level of correlation between those variables.

There are four indexes in the SEIFA set:

Index of Relative Socio-Economic Disadvantage

Index of Relative Socio-Economic Advantage/Disadvantage

Index of Economic Resources

Index of Education and Occupation

Of these, by far the most commonly used is the Index of Relative Socio-Economic Disadvantage (IRSED), and this is the one presented in profile.id®.

The IRSED compares the level of disadvantage between areas, and is not skewed by a high level of advantage. Technically a high score only measures a lack of disadvantage – NOT evidence of advantage).

ISRED is derived from the relative proportions of 17 Census characteristics such as:

The Index of Disadvantage is primarily used to rank areas to apply funding models which address need in the community, e.g. providing more funding for schools in disadvantaged areas.

A low SEIFA score for an area does not necessarily imply anything about individuals living in the area as the score is for the area overall. While a low score probably indicates many low income people living there, it does not imply that any particular resident is low income.

SEIFA indexes cannot be directly compared over time. The analysis is re-run every Census and different variables are found to be correlated. For this reason only the latest SEIFA figures are presented on the site. Older indexes are available on request, but only the relative ranking of areas can be compared, rather than the numbers directly.

Percentile is calculated by locating the suburb in the ABS State Suburb classification with the closest SEIFA index to the small area on this profile, and reporting the percentile for that suburb. In many cases, the exact area reported on here may be a custom geography and therefore not in the ABS State Suburb list. For this reason, the exact number of suburbs higher or lower than the area is not given, and this should be taken as a guide to the relative position of this area within Australia.

For more information about the use of SEIFA please refer to the ABS publication above or contact .id.

Seifa index of disadvantage

The SEIFA indexes are derived from Census data by a method called Principal Component Analysis which is a regression technique that derives an index from a set of variables related to the concept of disadvantage, based on the level of correlation between those variables.

There are four indexes in the SEIFA set:

Index of Relative Socio-Economic Disadvantage

Index of Relative Socio-Economic Advantage/Disadvantage

Index of Economic Resources

Index of Education and Occupation

Of these, by far the most commonly used is the Index of Relative Socio-Economic Disadvantage (IRSED), and this is the one presented in profile.id®.

The IRSED compares the level of disadvantage between areas, and is not skewed by a high level of advantage. Technically a high score only measures a lack of disadvantage – NOT evidence of advantage).

ISRED is derived from the relative proportions of 17 Census characteristics such as:

The Index of Disadvantage is primarily used to rank areas to apply funding models which address need in the community, e.g. providing more funding for schools in disadvantaged areas.

A low SEIFA score for an area does not necessarily imply anything about individuals living in the area as the score is for the area overall. While a low score probably indicates many low income people living there, it does not imply that any particular resident is low income.

SEIFA indexes cannot be directly compared over time. The analysis is re-run every Census and different variables are found to be correlated. For this reason only the latest SEIFA figures are presented on the site. Older indexes are available on request, but only the relative ranking of areas can be compared, rather than the numbers directly.

For more information about the use of SEIFA please refer to the ABS publication above or contact .id.

Residential location of workers

Derived from the Census:

'For the main job held last week, what was the person's workplace address?'

This dataset is known as Journey to Work, and is derived from Census question 41 – "For the main job held last week, what was the person's workplace address?" With residential address also known, Journey to Work comprises a matrix linking origin (residence) and work destination.

The data presented here in table form show the Statistical Local Area of residence for employed persons who work within City of Bayside. The map shows the spatial distribution of these workers.

Please note that the workforce in a Local Government Area calculated from Census data is generally considered to be an undercount, due to the number of people whose workplace address was not stated, could not be accurately coded, or stated a non-permanent workplace address ('no fixed place of work'). These people appear in the employment data at their residential location but cannot be coded to a work destination.

In 2011, a record number (over 1 million or 10% of employed persons) have been coded to an undefined work destination which cannot be mapped, and so these are excluded from the working population. For this reason some LGAs may notice an apparent drop in their Census-based workforce numbers between 2006 and 2011. While only 2011 data are presented here, this is most likely the reason.

If comparing work destination information with Method of Travel to work, please note the differing time periods – Workplace address relates to the week prior to Census, while Method of Travel relates to the morning of Census day. This has a negligible effect on the total counts but can explain some of the small numbers of strange LGA-LGA pairings which crop up such as people appearing to travel interstate to work. Some of these may be genuinely Fly-in/Fly-out workers (likely if the work destination is a known mining area), but others may have moved address in the differing timeframes assessed by the two questions.

Work location of residents

Derived from the Census:

'For the main job held last week, what was the person's workplace address?'

This dataset is known as Journey to Work, and is derived from Census question 41 – "For the main job held last week, what was the person's workplace address?" With residential address also known, Journey to Work comprises a matrix linking origin (residence) and work destination.

The data presented here in table form show the Statistical Local Area of work destination for employed persons who live within City of Bayside. The map shows the spatial distribution of where these residents work.

Please note that not all employed persons can be accurately coded to a workplace address. In 2011, a record number (over 1 million or 10% of employed persons) have been coded to an undefined work destination. These undefined locations are broken down by state, and shown in the table, but they cannot be mapped, as there is no information on the geographic location of work apart from their state.

For this reason, there may be difficulty comparing 2011 work destination data to 2006, and only 2011 data are presented here. This very large increase in undefined workplace location is believed to be due to the change to the new geography standard (ASGS), and the inefficient coding mechanisms used to code to it.

If comparing work destination information with Method of Travel to work, please note the differing time periods – Workplace address relates to the week prior to Census, while Method of Travel relates to the morning of Census day. This has a negligible effect on the total counts but can explain some of the small numbers of strange LGA-LGA pairings which crop up such as people appearing to travel interstate to work. Some of these may be genuinely Fly-in/Fly-out workers (likely if the work destination is a known mining area), but others may have moved address in the differing timeframes assessed by the two questions.

Work location of residents

Derived from the Census:

'For the main job held last week, what was the person's workplace address?'

This dataset is known as Journey to Work, and is derived from Census question 41 – "For the main job held last week, what was the person's workplace address?" With residential address also known, Journey to Work comprises a matrix linking origin (residence) and work destination.

The data presented here in table form show the Statistical Local Area of work destination for employed persons who live within City of Bayside. The map shows the spatial distribution of where these residents work.

Please note that not all employed persons can be accurately coded to a workplace address. In 2011, a record number (over 1 million or 10% of employed persons) have been coded to an undefined work destination. These undefined locations are broken down by state, and shown in the table, but they cannot be mapped, as there is no information on the geographic location of work apart from their state.

For this reason, there may be difficulty comparing 2011 work destination data to 2006, and only 2011 data are presented here. This very large increase in undefined workplace location is believed to be due to the change to the new geography standard (ASGS), and the inefficient coding mechanisms used to code to it.

If comparing work destination information with Method of Travel to work, please note the differing time periods – Workplace address relates to the week prior to Census, while Method of Travel relates to the morning of Census day. This has a negligible effect on the total counts but can explain some of the small numbers of strange LGA-LGA pairings which crop up such as people appearing to travel interstate to work. Some of these may be genuinely Fly-in/Fly-out workers (likely if the work destination is a known mining area), but others may have moved address in the differing timeframes assessed by the two questions.

Migration summary

Derived from the Census questions:

'Where does the person usually live?' and 'Where did the person usually live five years ago (at 9 August 2006)'.

Migration information is collected by the ABS by a series of questions asking where a person usually lived 1 year and 5 years prior to Census day. Only 5-year migration figures are presented here.

The table population is all persons resident in the area on Census night, and it is broken down by their previous location, within the area, within the same state, interstate, overseas or an unknown area.

The total of residents who moved within the same state includes a small percentage who were coded by the ABS to the “State undefined” category. There is a possibility that some of these may have been resident in the local area and have been incorrectly coded, but this is likely to have negligible impact on the overall percentages in each category.

Note that migration between 2006 and 2011 is only applicable for those persons aged 5 years and over on Census day 2011. Residents who were born in the interim cannot have a usual address 5 years ago. As the percentages are calculated on the total population, areas with high proportions of 0-4 year olds may have correspondingly lower percentages in the categories of movement.

Migration to and from

Derived from the Census questions:

'Where does the person usually live?' and 'Where did the person usually live five years ago (at 9 August 2006)'.

Migration information is collected by the ABS by a series of questions asking where a person usually lived 1 year and 5 years prior to Census day. Only 5-year migration figures are presented here.

This table shows the in, out and net migration figures for people (aged 5+) who moved within different geographic areas.

‘In migration’ relates to people who in 2011 lived within City of Bayside, but 5 years earlier (in 2006) lived elsewhere (in the area listed in the rows).

‘Out migration’ relates to people who in 2011 lived elsewhere in Australia (in the area listed in the rows), but who stated that in 2006 they lived in City of Bayside.

‘Net migration’ equals ‘In migration’ minus ‘Out migration’.

The LGA tables are ranked by the areas of largest positive and negative net migration respectively. The state tables show all states and territories, regardless of the level of migration gain or loss.

The total of residents who moved within the same state includes a small percentage who were coded by the ABS to the ‘State undefined’ category. There is a possibility that some of these may have been resident in the local area and have been incorrectly coded. For the purposes of this table, however, all residents in ‘State undefined’ 5 years ago who lived in City of Bayside in 2011 are counted as movement into the area.

The summary table shows in and out migration within the same state, to other states, and overseas. Please note that it is not possible to calculate a net migration figure for overseas, as the Census doesn’t count people who are overseas on Census day. So we only have data on those who moved in from overseas.

Migration by age

Derived from the Census questions:

'Where does the person usually live?' and 'Where did the person usually live five years ago (at 9 August 2006)'.

Migration information is collected by the ABS by a series of questions asking where a person usually lived 1 year and 5 years prior to Census day. Only 5-year migration figures are presented here.

The migration by age figures show the number of people who moved in and out of City of Bayside between 2006 and 2011, by their age group.

The age groups used correspond with the ages shown in the ‘Service Age Groups’ page under ‘What is the population?’. They are used because these age groups correlate highly with life stages when people are likely to make housing decisions and move (eg. leaving home, starting a family, retirement).

‘In migration’ relates to people who in 2011 lived within City of Bayside, but 5 years earlier (in 2006) lived elsewhere in Australia.

‘Out migration’ relates to people who in 2011 lived elsewhere in Australia (in the area listed in the rows), but who stated that in 2006 they lived in City of Bayside.

‘Net migration’ equals ‘In migration’ minus ‘Out migration’.

Please note that overseas migration is NOT included in this table, which relates only to migration within Australia. It is possible to have increasing population even if net migration of all age groups is negative, due to births and overseas migration.

Estimated Resident Population (ERP)

This dataset presents the last 10 years' official population estimates for the City of Bayside, including numerical and percentage change year on year, and comparison to the selected benchmark.

Estimated Resident Population is the official population of an area, if that area is based on one of the ABS standard geographic units (SA2s, LGAs). It adjusts for the net undercount found in Census data, people overseas on Census night, and is updated annually based on the number of registered births, deaths, and an estimate of overseas, interstate and intra-state migration.

While ERP is the most accurate measure of population at any point in time, it is subject to revision. Minor revisions are made each year to previous years' populations, and a final revision to the previous 5 years' results happens after each Census when the results are 'rebased' to the results of the most recent Census. This rebasing can alter populations significantly, depending on the Census findings, and indeed this is one of the reason we have a Census every 5 years.

Despite this revision, the ERP remains the official population count, and is used in allocation of funding at all levels of government, and the distribution of electorates by the Australian Electoral Commission.

Building approvals

Residential building approvals are compiled by the Australian Bureau of Statistics from permits issued by: local government authorities and other principal certifying authorities.

The data on this page counts the number of dwelling units created by the issue of building permits, regardless of the number of actual permits (eg. a single permit for a block of 50 apartments would count in this table as 50).

A residential building is a building consisting of one or more dwelling units. Residential buildings can be either houses or other residential buildings.

A house is defined as a stand-alone residential structure, separated on all sides from other dwellings by at least half a metre.

An other residential building is a building other than a house primarily used for long-term residential purposes. An other residential building contains more than one dwelling unit within the same structure – for example - semi-detached, row or terrace houses; flats, unit or apartments in blocks, or flats attached to houses or shops.

Exclusions:

Dwellings created by alterations/additions to existing dwellings are not included.

Dwellings created by building work which is largely non-residential in nature (eg. a caretaker’s dwelling built as part of a new hospital) are also not included as dwelling units, though they are included in value of approval data (not presented in profile.id).

For more information on the building approvals dataset, please refer to ABS catalogue number 8731.0 – Building Approvals, Australia.

Free demographic resources

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